JACC Adv. 2023 Mar 31;2(2):100277. doi: 10.1016/j.jacadv.2023.100277. eCollection 2023 Mar.

ABSTRACT

BACKGROUND: Despite advances in the treatment of oncology patients, therapy-related side effects may lead to premature morbidity. Inflammatory activation that has been linked to cardiovascular disease is crucial for the pathogenesis of both Hodgkin (HL) and non-Hodgkin lymphoma (NHL).

OBJECTIVES: The purpose of this study was to assess the vascular effects of chemotherapy in patients with HL and NHL by positron emission tomography/computed tomography with 18-fluorodeoxyglucose (18-FDG PET/CT) and to investigate interactions with systemic inflammation as assessed by circulating inflammatory markers.

METHODS: Between July 2015 and July 2019, 65 consecutive patients (mean age 56 ± 17.78 years) with confirmed diagnosis of either HL (n = 33) or NHL (n = 32) were prospectively studied. PET/CT imaging was performed at baseline, at an interim phase, and after first-line treatment. Aortic FDG uptake was assessed by measuring global aortic target-to-background ratio (GLA-TBR). Serum biomarkers interleukin (IL)-6 and IL-1b were measured at each phase.

RESULTS: Patients with HL demonstrated significant reduction in aortic TBR after first-line treatment (median GLA-TBR baseline: 1.98, median GLA-TBR third scan: 1.75, median difference = -0.20, 95% CI: -0.07 to -0.33, P = 0.006), which remained significant after adjustment for confounders (adj. R2 of model = 0.53). In contrast, patients with NHL did not demonstrate a significant aortic inflammation response (P = 0.306). Furthermore, patients with HL demonstrated a significant reduction in IL-6 (P = 0.048) and IL-1b (P = 0.045), whereas patients with NHL did not demonstrate significant reduction in IL-6 (P = 0.085) and IL-1b levels (P = 0.476).

CONCLUSIONS: Aortic inflammation, as assessed by 18-FDG PET/CT, is reduced in HL patients after first-line treatment but not in NHL patients. These findings imply that different pathophysiological pathways and different therapies might affect the arterial bed in different ways for patients with lymphoma.

PMID:38938303 | PMC:PMC11198565 | DOI:10.1016/j.jacadv.2023.100277

Clin Exp Allergy. 2024 Jun 27. doi: 10.1111/cea.14517. Online ahead of print.

ABSTRACT

Persistent and unresolved inflammation is a common underlying factor observed in several and seemingly unrelated human diseases, including cardiovascular and neurodegenerative diseases. Particularly, in atopic conditions, acute inflammatory responses such as those triggered by insect venom, food or drug allergies possess also a life-threatening potential. However, respiratory allergies predominantly exhibit late immune responses associated with chronic inflammation, that can eventually progress into a severe phenotype displaying similar features as those observed in other chronic inflammatory diseases, as is the case of uncontrolled severe asthma. This review aims to explore the different facets and systems involved in chronic allergic inflammation, including processes such as tissue remodelling and immune cell dysregulation, as well as genetic, metabolic and microbiota alterations, which are common to other inflammatory conditions. Our goal here was to deepen on the understanding of an entangled disease as is chronic allergic inflammation and expose potential avenues for the development of better diagnostic and intervention strategies.

PMID:38938054 | DOI:10.1111/cea.14517

Curr Top Dev Biol. 2024;160:87-109. doi: 10.1016/bs.ctdb.2024.05.004. Epub 2024 May 31.

ABSTRACT

A simple machine is a basic of device that takes mechanical advantage to apply force. Animals and plants self-assemble through the operation of a wide variety of simple machines. Embryos of different species actuate these simple machines to drive the geometric transformations that convert a disordered mass of cells into organized structures with discrete identities and function. These transformations are intrinsically coupled to sequential and overlapping steps of self-organization and self-assembly. The processes of self-organization have been explored through the molecular composition of cells and tissues and their information networks. By contrast, efforts to understand the simple machines underlying self-assembly must integrate molecular composition with the physical principles of mechanics. This primer is concerned with effort to elucidate the operation of these machines, focusing on the "problem" of morphogenesis. Advances in understanding self-assembly will ultimately connect molecular-, subcellular-, cellular- and meso-scale functions of plants and animals and their ability to interact with larger ecologies and environmental influences.

PMID:38937032 | DOI:10.1016/bs.ctdb.2024.05.004

J Invest Dermatol. 2024 Jun 25:S0022-202X(24)01739-1. doi: 10.1016/j.jid.2024.05.022. Online ahead of print.

NO ABSTRACT

PMID:38936767 | DOI:10.1016/j.jid.2024.05.022

Mol Cell. 2024 Jun 19:S1097-2765(24)00482-9. doi: 10.1016/j.molcel.2024.06.004. Online ahead of print.

ABSTRACT

Innate immunity is essential for the host against pathogens, cancer, and autoimmunity. The innate immune system encodes many sensor, adaptor, and effector proteins and relies on the assembly of higher-order signaling complexes to activate immune defense. Recent evidence demonstrates that many of the core complexes involved in innate immunity are organized as liquid-like condensates through a mechanism known as phase separation. Here, we discuss phase-separated condensates and their diverse functions. We compare the biochemical, structural, and mechanistic details of solid and liquid-like assemblies to explore the role of phase separation in innate immunity. We summarize the emerging evidence for the hypothesis that phase separation is a conserved mechanism that controls immune responses across the tree of life. The discovery of phase separation in innate immunity provides a new foundation to explain the rules that govern immune system activation and will enable the development of therapeutics to treat immune-related diseases properly.

PMID:38936362 | DOI:10.1016/j.molcel.2024.06.004

J Plant Physiol. 2024 Jun 20;300:154299. doi: 10.1016/j.jplph.2024.154299. Online ahead of print.

ABSTRACT

The F-box protein (FBP) family plays diverse functions in the plant kingdom, with the function of many members still unrevealed. In this study, a specific FBP called PmFBK2, containing Kelch repeats from Persicaria minor, was functionally investigated. Employing the yeast two-hybrid (Y2H) assay, PmFBK2 was found to interact with Skp1-like proteins from P. minor, suggesting its potential to form an E3 ubiquitin ligase, known as the SCF complex. Y2H and co-immunoprecipitation tests revealed that PmFBK2 interacts with full-length PmGID1b. The interaction marks the first documented binding between these two protein types, which have never been reported in other plants before, and they exhibited a negative effect on gibberellin (GA) signal transduction. The overexpression of PmFBK2 in the kmd3 mutant, a homolog from Arabidopsis, demonstrated the ability of PmFBK2 to restore the function of the mutated KMD3 gene. The function restoration was supported by morphophysiological and gene expression analyses, which exhibited patterns similar to the wild type (WT) compared to the kmd3 mutant. Interestingly, the overexpression of PmFBK2 or PmGID1b in Arabidopsis had opposite effects on rosette diameter, seed weight, and plant height. This study provides new insights into the complex GA signalling. It highlights the crucial roles of the interaction between FBP and the GA receptor (GID1b) in regulating GA responses. These findings have implications for developing strategies to enhance plant growth and yield by modulating GA signalling in crops.

PMID:38936241 | DOI:10.1016/j.jplph.2024.154299

J Transl Med. 2024 Jun 27;22(1):600. doi: 10.1186/s12967-024-05403-4.

ABSTRACT

BACKGROUND: Interstitial lung disease (ILD) is the primary cause of mortality in systemic sclerosis (SSc), an autoimmune disease characterized by tissue fibrosis. SSc-related ILD (SSc-ILD) occurs more frequently in females aged 30-55 years, whereas idiopathic pulmonary fibrosis (IPF) is more prevalent in males aged 60-75 years. SSc-ILD occurs earlier than IPF and progresses rapidly. FCN1, FABP4, and SPP1 macrophages are involved in the pathogenesis of lung fibrosis; SPP1 macrophages demonstrate upregulated expression in both SSc-ILD and IPF. To identify the differences between SSc-ILD and IPF using single-cell analysis, clarify their distinct pathogeneses, and propose directions for prevention and treatment.

METHODS: We performed single-cell RNA sequencing on NCBI Gene Expression Omnibus (GEO) databases GSE159354 and GSE212109, and analyzed lung tissue samples across healthy controls, IPF, and SSc-ILD. The primary measures were the filtered genes integrated with batch correction and annotated cell types for distinguishing patients with SSc-ILD from healthy controls. We proposed an SSc-ILD pathogenesis using cell-cell interaction inferences, and predicted transcription factors regulating target genes using SCENIC. Drug target prediction of the TF gene was performed using Drug Bank Online.

RESULTS: A subset of macrophages activates the MAPK signaling pathway under oxidative stress. Owing to the lack of inhibitory feedback from ANNEXIN and the autoimmune characteristics, this leads to an earlier onset of lung fibrosis compared to IPF. During initial lung injury, fibroblasts begin to activate the IL6 pathway under the influence of SPP1 alveolar macrophages, but IL6 appears unrelated to other inflammatory and immune cells. This may explain why tocilizumab (an anti-IL6-receptor antibody) only preserves lung function in patients with early SSc-ILD. Finally, we identified BCLAF1 and NFE2L2 as influencers of MAPK activation in macrophages. Metformin downregulates NFE2L2 and could serve as a repurposed drug candidate.

CONCLUSIONS: SPP1 alveolar macrophages play a role in the profibrotic activity of IPF and SSc-ILD. However, SSc-ILD is influenced by autoimmunity and oxidative stress, leading to the continuous activation of MAPK in macrophages. This may result in an earlier onset of lung fibrosis than in IPF. Such differences could serve as potential research directions for early prevention and treatment.

PMID:38937794 | DOI:10.1186/s12967-024-05403-4

Genet Sel Evol. 2024 Jun 27;56(1):50. doi: 10.1186/s12711-024-00916-4.

ABSTRACT

BACKGROUND: Genome sequence variants affecting complex traits (quantitative trait loci, QTL) are enriched in functional regions of the genome, such as those marked by certain histone modifications. These variants are believed to influence gene expression. However, due to the linkage disequilibrium among nearby variants, pinpointing the precise location of QTL is challenging. We aimed to identify allele-specific binding (ASB) QTL (asbQTL) that cause variation in the level of histone modification, as measured by the height of peaks assayed by ChIP-seq (chromatin immunoprecipitation sequencing). We identified DNA sequences that predict the difference between alleles in ChIP-seq peak height in H3K4me3 and H3K27ac histone modifications in the mammary glands of cows.

RESULTS: We used a gapped k-mer support vector machine, a novel best linear unbiased prediction model, and a multiple linear regression model that combines the other two approaches to predict variant impacts on peak height. For each method, a subset of 1000 sites with the highest magnitude of predicted ASB was considered as candidate asbQTL. The accuracy of this prediction was measured by the proportion where the predicted direction matched the observed direction. Prediction accuracy ranged between 0.59 and 0.74, suggesting that these 1000 sites are enriched for asbQTL. Using independent data, we investigated functional enrichment in the candidate asbQTL set and three control groups, including non-causal ASB sites, non-ASB variants under a peak, and SNPs (single nucleotide polymorphisms) not under a peak. For H3K4me3, a higher proportion of the candidate asbQTL were confirmed as ASB when compared to the non-causal ASB sites (P < 0.01). However, these candidate asbQTL did not enrich for the other annotations, including expression QTL (eQTL), allele-specific expression QTL (aseQTL) and sites conserved across mammals (P > 0.05).

CONCLUSIONS: We identified putatively causal sites for asbQTL using the DNA sequence surrounding these sites. Our results suggest that many sites influencing histone modifications may not directly affect gene expression. However, it is important to acknowledge that distinguishing between putative causal ASB sites and other non-causal ASB sites in high linkage disequilibrium with the causal sites regarding their impact on gene expression may be challenging due to limitations in statistical power.

PMID:38937662 | DOI:10.1186/s12711-024-00916-4

Nat Metab. 2024 Jun 27. doi: 10.1038/s42255-024-01072-1. Online ahead of print.

ABSTRACT

The low-carbohydrate ketogenic diet (KD) has long been practiced for weight loss, but the underlying mechanisms remain elusive. Gut microbiota and metabolites have been suggested to mediate the metabolic changes caused by KD consumption, although the particular gut microbes or metabolites involved are unclear. Here, we show that KD consumption enhances serum levels of taurodeoxycholic acid (TDCA) and tauroursodeoxycholic acid (TUDCA) in mice to decrease body weight and fasting glucose levels. Mechanistically, KD feeding decreases the abundance of a bile salt hydrolase (BSH)-coding gut bacterium, Lactobacillus murinus ASF361. The reduction of L. murinus ASF361 or inhibition of BSH activity increases the circulating levels of TDCA and TUDCA, thereby reducing energy absorption by inhibiting intestinal carbonic anhydrase 1 expression, which leads to weight loss. TDCA and TUDCA treatments have been found to protect against obesity and its complications in multiple mouse models. Additionally, the associations among the abovementioned bile acids, microbial BSH and metabolic traits were consistently observed both in an observational study of healthy human participants (n = 416) and in a low-carbohydrate KD interventional study of participants who were either overweight or with obesity (n = 25). In summary, we uncover a unique host-gut microbiota metabolic interaction mechanism for KD consumption to decrease body weight and fasting glucose levels. Our findings support TDCA and TUDCA as two promising drug candidates for obesity and its complications in addition to a KD.

PMID:38937659 | DOI:10.1038/s42255-024-01072-1

Br J Haematol. 2024 Jun 27. doi: 10.1111/bjh.19577. Online ahead of print.

NO ABSTRACT

PMID:38937136 | DOI:10.1111/bjh.19577

Am J Respir Crit Care Med. 2024 Jun 27. doi: 10.1164/rccm.202401-0011OC. Online ahead of print.

ABSTRACT

Rationale Dysanapsis refers to a mismatch between airway tree caliber and lung size arising early in life. Dysanapsis assessed by computed tomography (CT) is evident by early adulthood and associated with chronic obstructive pulmonary disease (COPD) risk later in life. Objective By examining the genetic factors associated with CT-assessed dysanapsis, we aimed to elucidate its molecular underpinnings and physiological significance across the lifespan. Methods We performed a genome-wide association study (GWAS) of CT-assessed dysanapsis in 11,951 adults, including individuals from two population-based and two COPD-enriched studies. We applied colocalization analysis to integrate GWAS and gene expression data from whole blood and lung. Genetic variants associated with dysanapsis were combined into a genetic risk score that was applied to examine association with lung function in children from a population-based birth cohort (n=1,278) and adults from the UK Biobank (n=369,157). Measurements and Main Results CT-assessed dysanapsis was associated with genetic variants from 21 independent signals in 19 gene regions, implicating HHIP, DSP, and NPNT as potential molecular targets based on colocalization of their expression. Higher dysanapsis genetic risk score was associated with obstructive spirometry among 5 year old children and among adults in the 5th, 6th and 7th decades of life. Conclusions CT-assessed dysanapsis is associated with variation in genes previously implicated in lung development and dysanapsis genetic risk is associated with obstructive lung function from early life through older adulthood. Dysanapsis may represent an endo-phenotype link between the genetic variations associated with lung function and COPD.

PMID:38935874 | DOI:10.1164/rccm.202401-0011OC

PLoS One. 2024 Jun 27;19(6):e0306345. doi: 10.1371/journal.pone.0306345. eCollection 2024.

ABSTRACT

Chronic liver diseases are caused by hepatic viral infection, chemicals, and metabolic stress. The protein Grb2-associated binder 1 (Gab1) binds to various growth factor receptors, and triggers cell differentiation/survival signaling pathways. To identify signaling molecules involved in the progression of liver diseases, we performed reverse-phase protein microarray (RPMA)-based screening of hepatocytes isolated from humanized mice after acute HCV infection. Acute viral infection in humanized liver mice significantly decreased the level of hepatocyte p-Gab1. Moreover, hepatoma cells upon HCV infection decreased Gab1 mRNA at later times of infection (D3 to D5) and p-Gab1 level was inversely related to the production of TGF-β. In contrast, the level of p-Gab1 was increased in CCL4-induced fibrotic liver. Hepatoma cells showed elevation of p-Gab1, along with an increase in STAT3 and ERK activation, upon treatment with HGF (ligand of HGF receptor/c-Met) and CCL4. In Gab1 knockdown hepatoma cells, cell proliferative signaling activity was reduced but the level of activated caspase-3 was increased. These findings suggest that hepatocyte Gab1 expression may play a role in promoting liver fibrosis progression by triggering ERK activation and inhibiting apoptosis. It implies that the Gab1-mediated signaling pathway would be a promising therapeutic target to treat chronic liver diseases.

PMID:38935609 | DOI:10.1371/journal.pone.0306345

Proc Natl Acad Sci U S A. 2024 Jul 9;121(28):e2410274121. doi: 10.1073/pnas.2410274121. Epub 2024 Jun 27.

NO ABSTRACT

PMID:38935582 | DOI:10.1073/pnas.2410274121

J Cell Biol. 2024 Oct 7;223(10):e202403115. doi: 10.1083/jcb.202403115. Epub 2024 Jun 27.

ABSTRACT

Regulated cell shape change requires the induction of cortical cytoskeletal domains. Often, local changes to plasma membrane (PM) topography are involved. Centrosomes organize cortical domains and can affect PM topography by locally pulling the PM inward. Are these centrosome effects coupled? At the syncytial Drosophila embryo cortex, centrosome-induced actin caps grow into dome-like compartments for mitoses. We found the nascent cap to be a collection of PM folds and tubules formed over the astral centrosomal MT array. The localized infoldings require centrosome and dynein activities, and myosin-based surface tension prevents them elsewhere. Centrosome-engaged PM infoldings become specifically enriched with an Arp2/3 induction pathway. Arp2/3 actin network growth between the infoldings counterbalances centrosomal pulling forces and disperses the folds for actin cap expansion. Abnormal domain topography with either centrosome or Arp2/3 disruption correlates with decreased exocytic vesicle association. Together, our data implicate centrosome-organized PM infoldings in coordinating Arp2/3 network growth and exocytosis for cortical domain assembly.

PMID:38935075 | DOI:10.1083/jcb.202403115

Brief Bioinform. 2024 May 23;25(4):bbae309. doi: 10.1093/bib/bbae309.

ABSTRACT

Inferring gene regulatory network (GRN) is one of the important challenges in systems biology, and many outstanding computational methods have been proposed; however there remains some challenges especially in real datasets. In this study, we propose Directed Graph Convolutional neural network-based method for GRN inference (DGCGRN). To better understand and process the directed graph structure data of GRN, a directed graph convolutional neural network is conducted which retains the structural information of the directed graph while also making full use of neighbor node features. The local augmentation strategy is adopted in graph neural network to solve the problem of poor prediction accuracy caused by a large number of low-degree nodes in GRN. In addition, for real data such as E.coli, sequence features are obtained by extracting hidden features using Bi-GRU and calculating the statistical physicochemical characteristics of gene sequence. At the training stage, a dynamic update strategy is used to convert the obtained edge prediction scores into edge weights to guide the subsequent training process of the model. The results on synthetic benchmark datasets and real datasets show that the prediction performance of DGCGRN is significantly better than existing models. Furthermore, the case studies on bladder uroepithelial carcinoma and lung cancer cells also illustrate the performance of the proposed model.

PMID:38935070 | DOI:10.1093/bib/bbae309

mSystems. 2024 Jun 27:e0135823. doi: 10.1128/msystems.01358-23. Online ahead of print.

ABSTRACT

The alarming rise of antibiotic-resistant bacterial infections is driving efforts to develop alternatives to conventional antibiotics. In this context, antimicrobial peptides (AMPs) have emerged as promising candidates for their ability to target a broad range of microorganisms. However, the development of AMPs with optimal potency, selectivity, and/or stability profiles remains a challenge. To address it, computational tools for predicting AMP properties and designing novel peptides have gained increasing attention. PyAMPA is a novel platform for AMP discovery. It consists of five modules, namely AMPScreen, AMPValidate, AMPSolve, AMPMutate, and AMPOptimize, that allow high-throughput proteome inspection, candidate screening, and optimization through point-mutation and genetic algorithms. The platform also offers additional tools for predicting and evaluating AMP properties, including antimicrobial and cytotoxic activity, and peptide half-life. By providing innovative and accessible inroads into AMP motifs in proteomes, PyAMPA will enable advances in AMP development and potential translation into clinically useful molecules. PyAMPA is available at: https://github.com/SysBioUAB/PyAMPA.

IMPORTANCE: This paper introduces PyAMPA, a new bioinformatics platform designed for the discovery and optimization of antimicrobial peptides (AMPs). It addresses the urgent need for new antimicrobials due to the rise of antibiotic-resistant infections. PyAMPA, with its five predictive modules -AMPScreen, AMPValidate, AMPSolve, AMPMutate and AMPOptimize, enables high-throughput screening of proteomes to identify potential AMP motifs and optimize them for clinical use. Its unique approach, combining prediction, design, and optimization tools, makes PyAMPA a robust solution for developing new AMP-based therapies, offering a significant advance in combatting antibiotic resistance.

PMID:38934543 | DOI:10.1128/msystems.01358-23

ACS Synth Biol. 2024 Jun 27. doi: 10.1021/acssynbio.3c00572. Online ahead of print.

ABSTRACT

As the availability of data sets increases, meta-analysis leveraging aggregated and interoperable data types is proving valuable. This study leveraged a meta-analysis workflow to identify mutations that could improve robustness to reactive oxygen species (ROS) stresses using an industrially important melatonin production strain as an example. ROS stresses often occur during cultivation and negatively affect strain performance. Cellular response to ROS is also linked to the SOS response and resistance to pH fluctuations, which is important to strain robustness in large-scale biomanufacturing. This work integrated more than 7000 E. coli adaptive laboratory evolution (ALE) mutations across 59 experiments to statistically associate mutated genes to 2 ROS tolerance ALE conditions from 72 unique conditions. Mutant oxyR, fur, iscR, and ygfZ were significantly associated and hypothesized to contribute fitness in ROS stress. Across these genes, 259 total mutations were inspected in conjunction with transcriptomics from 46 iModulon experiments. Ten mutations were chosen for reintroduction based on mutation clustering and coinciding transcriptional changes as evidence of fitness impact. Strains with mutations reintroduced into oxyR, fur, iscR, and ygfZ exhibited increased tolerance to H2O2 and acid stress and reduced SOS response, all of which are related to ROS. Additionally, new evidence was generated toward understanding the function of ygfZ, an uncharacterized gene. This meta-analysis approach utilized aggregated and interoperable multiomics data sets to identify mutations conferring industrially relevant phenotypes with the least drawbacks, describing an approach for data-driven strain engineering to optimize microbial cell factories.

PMID:38934464 | DOI:10.1021/acssynbio.3c00572

Fundam Res. 2021 Dec 30;2(1):2-13. doi: 10.1016/j.fmre.2021.12.007. eCollection 2022 Jan.

ABSTRACT

To enable diverse functions and precise regulation, an RNA sequence often folds into complex yet distinct structures in different cellular states. Probing RNA in its native environment is essential to uncovering RNA structures of biological contexts. However, current methods generally require large amounts of input RNA and are challenging for physiologically relevant use. Here, we report smartSHAPE, a new RNA structure probing method that requires very low amounts of RNA input due to the largely reduced artefact of probing signals and increased efficiency of library construction. Using smartSHAPE, we showcased the profiling of the RNA structure landscape of mouse intestinal macrophages upon inflammation, and provided evidence that RNA conformational changes regulate immune responses. These results demonstrate that smartSHAPE can greatly expand the scope of RNA structure-based investigations in practical biological systems, and also provide a research paradigm for the study of post-transcriptional regulation.

PMID:38933905 | PMC:PMC11197792 | DOI:10.1016/j.fmre.2021.12.007

Fundam Res. 2022 Aug 9;2(6):894-902. doi: 10.1016/j.fmre.2022.07.011. eCollection 2022 Nov.

ABSTRACT

The difficulty of converting scientific research findings into novel pharmacological treatments for rare and life-threatening diseases is enormous. Biomarkers related to multiple biological processes involved in cell growth, proliferation, and disease occurrence have been identified in recent years with the development of immunology, molecular biology, and genomics technologies. Biomarkers are capable of reflecting normal physiological processes, pathological processes, and the response to therapeutic intervention; as such, they play vital roles in disease diagnosis, prevention, drug response, and other aspects of biomedicine. The discovery of valuable biomarkers has become a focal point of current research. Numerous studies have identified molecular biomarkers based on the differential expression/concentration of molecules (e.g., genes/proteins) for disease state diagnosis, characterization, and treatment. Although technological breakthroughs in molecular analysis platforms have enabled the identification of a large number of candidate biomarkers for rare diseases, only a small number of these candidates have been properly validated for use in patient treatment. The traditional molecular biomarkers may lose vital information by ignoring molecular associations/interactions, and thus the concept of network biomarkers based on differential associations/correlations of molecule pairs has been established. This approach promises to be more stable and reliable in diagnosing disease states. Furthermore, the newly-emerged dynamic network biomarkers (DNBs) based on differential fluctuations/correlations of molecular groups are able to recognize pre-disease states or critical states instead of disease states, thereby achieving rare disease prediction or predictive/preventative medicine and providing deep insight into the dynamic characteristics of disease initiation and progression.

PMID:38933388 | PMC:PMC11197705 | DOI:10.1016/j.fmre.2022.07.011

Fundam Res. 2023 Jun 12;3(5):727-737. doi: 10.1016/j.fmre.2023.06.001. eCollection 2023 Sep.

ABSTRACT

RNA molecules serve a wide range of functions that are closely linked to their structures. The basic structural units of RNA consist of single- and double-stranded regions. In order to carry out advanced functions such as catalysis and ligand binding, certain types of RNAs can adopt higher-order structures. The analysis of RNA structures has progressed alongside advancements in structural biology techniques, but it comes with its own set of challenges and corresponding solutions. In this review, we will discuss recent advances in RNA structure analysis techniques, including structural probing methods, X-ray crystallography, nuclear magnetic resonance, cryo-electron microscopy, and small-angle X-ray scattering. Often, a combination of multiple techniques is employed for the integrated analysis of RNA structures. We also survey important RNA structures that have been recently determined using various techniques.

PMID:38933295 | PMC:PMC11197651 | DOI:10.1016/j.fmre.2023.06.001